Friday 23 November 2018: Study day on the future of reading & writing, UGent, with lecture by Nick Montfort and workshop on algoliterary practises by Gijs de Heij and An Mertens

8 to 12 October 2018: Gijs de Heij and An Mertens offer a workshop at the Mundaneum in Mons with students of ARTS2, Numediart and other schools, on the use of statistical machine learning models and archival materials for literary writing. The artists will propose existing tools and practices and Oulipian methodologies for the play of algoliterary writing games. Participants in the workshop will be able to continue developing their works after the workshop week, and participate in the exhibition that Algolit will hold at the Mundaneum around March 2019. More information: Mundaneum_workshop

Friday 28 September:Naive Bayes as a storyteller

10-18h, Brussels, Constant wtc25, Tower 1, Bd Roi Albert-II/Kon Albert-II laan 30, 1000 Brussels
https://pad.constantvzw.org/p/180928_algolit_naive_bayes
In machine learning Naive Bayes is a simple probabilistic classifier that is widely applied for spam filtering and sentiment analysis. Based on the documentation of the previous session, we now use this technique as a recipe for potential literary creation - that can be physical, computational or analogical.

Topics for 2016-2017

Past Meetings

9-12 November 2017: Algoliterary Encounter

In the framework of Saison Numérique the Maison du Livre opens its space for Algolit during three days in a row. The group presents lectures, workshops and a small exhibition about the narrative perspective of machine learning models. These are selflearning algorithms based on algebra and statistics. They often function as opaque 'blackbox' algorithms, while they shape applications that are daily used on a worldwide scale, like search engines on the web, translation machines, advertising profiling, facial recognition etc.

Because machine learning is so present, the members of Algolit felt the need to distillate reading and writing experiments from it. By executing parts of their creation process in a literary context, they become more legible. It is way to experience a few moments that are usually hidden in the making of the model, and that co-design contemporary stories in the way they influence the organisation of information.

Thursday 3 November 2016: we will start from Uncertainty Detected, a supervised machine learning script (using Python and Scikit Learn) that predicts uncertain sentences in scientific papers. By looking at the code and visualisations of the data, we will propose some concrete parts of the process for literary, textual and design applications. Hosts: Gijs & An